Evaluation

Recommender systems research and practice are fast-developing topics with growing adoption in a wide variety of information access …

Evaluation is important when developing and deploying recommender systems. The PERSPECTIVES workshop sheds light on the different, …

Evaluation of recommender systems is a central activity when developing recommender systems, both in industry and academia. The second …

Reproducibility is a key requirement for scientific progress. It allows the reproduction of the works of others, and, as a consequence, …

Evaluation is a cornerstone in the process of developing and deploying recommender systems. The PERSPECTIVES workshop brought together …

Recommender Systems have to deal with a wide variety of users and user types that express their preferences in different ways. This …

Recommender systems addvalue to vast content resources by matching users with items of interest. In recent years, immense progress has …

Recommender systems research is by and large based on comparisons of recommendation algorithms’ predictive accuracies: the better …

We present a study of how recommendations are received in real life by users across different news domains (traditional online …

Currently, it is diffcult to put in context and compare the results from a given evaluation of a recommender system, mainly because too …

During the last decade, recommender systems have become a ubiquitous feature in the online world. Research on systems and algorithms in …

Experiment replication and reproduction are key requirements for empirical research methodology, and an important open issue in the …

Evaluating adaptive and personalized information retrieval tech-niques is known to be a difficult endeavor. The rapid evolution of …

Collaborative filtering recommender systems often use nearest neighbor methods to identify candidate items. In this paper we present an …

In this work we describe an approach at multi-objective recommender system evaluation based on a previously introduced 3D benchmarking …

Traditional recommender system evaluation focuses on raising the accuracy, or lowering the rating prediction error of the …

Recommender systems are commonly evaluated by trying to predict known, withheld, ratings for a set of users. Measures such as the …

Collaborative Filtering Recommender Systems come in a wide variety of variants. In this paper we present a system for visualizing and …

Recommender System Challenges such as the Netix Prize, KDD Cup, etc. have contributed vastly to the development and adoptability of …